Deep Neural Network With Structural Similarity Difference and Orientation-Based Loss for Position Error Classification in the Radiotherapy of Graves’ Ophthalmopathy Patients

Liu, Wenjie; Zhang, Lei; Dai, Guyu; Zhang, Xiangbin; Li, Guangjun; Zhang, Yi

doi:10.1109/jbhi.2021.3137451

Cited by 6 publications

(7 citation statements)

References 42 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A common disadvantage of the aforementioned studies was that their AI models focused on only one specific retinal disorder leaving others unable to be recognized, which reduced their feasibility and availability in real-world practice as community screening (Kuwayama et al, 2019;Liu et al, 2022). Our AI model could identify multiple retinal disorders simultaneously in single detection, which was more appropriate for the scene of community screening with the unpredicted situations and comprehensive diseases and saved more time and occupied fewer human resources.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, we also compare some state-of-the-art methods in the literature, including R2UNet (Alom et al, 2019), DUNet (Jin et al, 2019), NFN+ , CAR-UNet (Guo et al, 2021a), RVSeg-Net , SCS-Net (Wu et al, 2021), AG-Net and FR-UNet (Liu et al, 2022). Only the four methods in the previous paragraph come from our reproduced results, and the results of all other methods come from the corresponding papers.…”

Section: Comparison With the State-of-the-art Methodsmentioning

confidence: 99%

“…Nowadays the clinical diagnosis of MGD still lacks objective evaluations, and depends on the subjective judgment. Recently, the technology of meibography has been constantly developed, and is able to provide objective means to evaluate MG status using artificial intelligence (AI) Liu et al, 2022;Zhang et al, 2022). In order to obtain objective results, we evaluated the relationship of MG parameters identified by AI with age and gender in the current study.…”

Section: Abstract Meibomian Glands Meibomian Gland Dysfunction Meibog...mentioning

confidence: 99%

See 2 more Smart Citations

Artificial Intelligence Applications in Chronic Ocular Diseases

2024

Frontiers Research Topics

View full text Add to dashboard Cite

Frontiers is more than just an open access publisher of scholarly articles: it is a pioneering approach to the world of academia, radically improving the way scholarly research is managed. The grand vision of Frontiers is a world where all people have an equal opportunity to seek, share and generate knowledge. Frontiers provides immediate and permanent online open access to all its publications, but this alone is not enough to realize our grand goals. Frontiers journal seriesThe Frontiers journal series is a multi-tier and interdisciplinary set of openaccess, online journals, promising a paradigm shift from the current review, selection and dissemination processes in academic publishing. All Frontiers journals are driven by researchers for researchers; therefore, they constitute a service to the scholarly community. At the same time, the Frontiers journal series operates on a revolutionary invention, the tiered publishing system, initially addressing specific communities of scholars, and gradually climbing up to broader public understanding, thus serving the interests of the lay society, too. Dedication to qualityEach Frontiers article is a landmark of the highest quality, thanks to genuinely collaborative interactions between authors and review editors, who include some of the world's best academicians. Research must be certified by peers before entering a stream of knowledge that may eventually reach the public -and shape society; therefore, Frontiers only applies the most rigorous and unbiased reviews. Frontiers revolutionizes research publishing by freely delivering the most outstanding research, evaluated with no bias from both the academic and social point of view. By applying the most advanced information technologies, Frontiers is catapulting scholarly publishing into a new generation. What are Frontiers Research Topics?Frontiers Research Topics are very popular trademarks of the Frontiers journals series: they are collections of at least ten articles, all centered on a particular subject. With their unique mix of varied contributions from Original Research to Review Articles, Frontiers Research Topics unify the most influential researchers, the latest key findings and historical advances in a hot research area.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Comparison With the State-of-the-art Methodsmentioning

confidence: 99%

Section: Abstract Meibomian Glands Meibomian Gland Dysfunction Meibog...mentioning

confidence: 99%

See 1 more Smart Citation

Artificial Intelligence Applications in Chronic Ocular Diseases

2024

Frontiers Research Topics

View full text Add to dashboard Cite

show abstract

“…The classification accuracies of the CNN model performed well in this competition. Additionally, Liu et al (2022) developed a deep neural network (DNN) algorithm with structural similarity difference and orientation-based loss, which could provide more features and information from EPID images. A total of 2240 EPID fluence maps were enrolled and subjected to the DNN model for training and testing.…”

Section: Application Of Ai Algorithms In Treating Taomentioning

confidence: 99%

Research progress and application of artificial intelligence in thyroid associated ophthalmopathy

Diao

Chen

Shen

et al. 2023

Front. Cell Dev. Biol.

View full text Add to dashboard Cite

Thyroid-associated ophthalmopathy (TAO) is a complicated orbitopathy related to dysthyroid, which severely destroys the facial appearance and life quality without medical interference. The diagnosis and management of thyroid-associated ophthalmopathy are extremely intricate, as the number of professional ophthalmologists is limited and inadequate compared with the number of patients. Nowadays, medical applications based on artificial intelligence (AI) algorithms have been developed, which have proved effective in screening many chronic eye diseases. The advanced characteristics of automated artificial intelligence devices, such as rapidity, portability, and multi-platform compatibility, have led to significant progress in the early diagnosis and elaborate evaluation of these diseases in clinic. This study aimed to provide an overview of recent artificial intelligence applications in clinical diagnosis, activity and severity grading, and prediction of therapeutic outcomes in thyroid-associated ophthalmopathy. It also discussed the current challenges and future prospects of the development of artificial intelligence applications in treating thyroid-associated ophthalmopathy.

show abstract

“…Liu et al [ 3 ] introduced position uncertainties in left-right (LR), anterior-posterior (AP), and superior-inferior (SI) directions in the delivery of Graves' ophthalmopathy radiotherapy plans to a head phantom during treatment, and used ML model and convolutional neural network (CNN) model to classify patient position errors. They also developed a deep neural network model with structural similarity difference and orientation-based loss to classify these errors to improve the classification performance.…”

mentioning

confidence: 99%